From 2cb064f843995c85324dfa34c2ecd9360fe12a25 Mon Sep 17 00:00:00 2001 From: Felix Patzelt Date: Fri, 29 Sep 2017 02:42:08 +0200 Subject: [PATCH] copyediting --- README.rst | 4 ++-- .../two_point_vs_three_point_correlations.ipynb | 15 +++++++++++---- 2 files changed, 13 insertions(+), 6 deletions(-) diff --git a/README.rst b/README.rst index c2cc47b..136ba35 100644 --- a/README.rst +++ b/README.rst @@ -9,12 +9,12 @@ for normalisation, mean removal, averaging, and zero-padding. In particular, averaging over pandas groups of different sizes (e.g. different days) is supported. -The algorithms to calculate three-point correlations described in: +The algorithms to calculate three-point correlations are described in: Patzelt, F. and Bouchaud, J-P.: Nonlinear price impact from linear models. Journal of Statistical Mechanics (2017). - Preprint at arXiv:1706.04163. + Preprint at arXiv:1708.02411. ====================== ====================================================== diff --git a/examples/two_point_vs_three_point_correlations.ipynb b/examples/two_point_vs_three_point_correlations.ipynb index 1249202..d828011 100644 --- a/examples/two_point_vs_three_point_correlations.ipynb +++ b/examples/two_point_vs_three_point_correlations.ipynb @@ -11,12 +11,19 @@ "> Patzelt, F. and Bouchaud, J-P. (2017):\n", "> Nonlinear price impact from linear models.\n", "> *Journal of Statistical Mechanics.*\n", - "> Preprint at arXiv:1706.04163.\n", + "> Preprint at arXiv:1708.02411.\n", "\n", - "The notation is consistent with that paper and the related literature. To just understand the code below, consider a series of signs `s` $\\in [-1,1]$ and change indicators `c` $\\in [n,c]$. We use `0` and `1`to represent no change (n) and change (c).\n", + "To just understand the code below, consider a series of signs `s` $\\in [-1,1]$ and change indicators `c` $\\in [n,c]$. We use `0` and `1`to represent no change (n) and change (c). We denote the elementwise product by `sc`.\n", "\n", - "Below we calculate two-point correlation matrices \n", - "$C_{\\pi \\pi' \\pi''}(\\ell,j)$ was approximated by the two-point cross-correlation $C_{\\pi \\pi'}(j) := \\langle \\delta_{\\pi(t)\\, \\pi}\\, \\epsilon(t)\\: \\delta_{\\pi(t-j)\\, \\pi'}\\, \\epsilon(t-j) \\rangle$" + "Below we calculate three-point correlation matrices \n", + "\n", + "$C_{c, s c, s c}(\\ell,j)$, \n", + "\n", + "and the two-point correlation matrix\n", + "\n", + "$C_{s c, s c}(\\ell,j)$ \n", + "\n", + "that was used to approximated by the prior before the developement of the spectral method implemented by `scorr.x3corr`." ] }, {